879 research outputs found
Corporate Bankruptcy Prediction
Bankruptcy prediction is one of the most important research areas in corporate finance. Bankruptcies are an indispensable element of the functioning of the market economy, and at the same time generate significant losses for stakeholders. Hence, this book was established to collect the results of research on the latest trends in predicting the bankruptcy of enterprises. It suggests models developed for different countries using both traditional and more advanced methods. Problems connected with predicting bankruptcy during periods of prosperity and recession, the selection of appropriate explanatory variables, as well as the dynamization of models are presented. The reliability of financial data and the validity of the audit are also referenced. Thus, I hope that this book will inspire you to undertake new research in the field of forecasting the risk of bankruptcy
Urban food strategies in Central and Eastern Europe: what's specific and what's at stake?
Integrating a larger set of instruments into
Rural Development Programmes implied an increasing
focus on monitoring and evaluation. Against the highly
diversified experience with regard to implementation
of policy instruments the Common Monitoring
and Evaluation Framework has been set up by the EU
Commission as a strategic and streamlined method of
evaluating programmes’ impacts. Its indicator-based
approach mainly reflects the concept of a linear,
measure-based intervention logic that falls short of
the true nature of RDP operation and impact capacity
on rural changes. Besides the different phases of the
policy process, i.e. policy design, delivery and evaluation,
the regional context with its specific set of challenges
and opportunities seems critical to the understanding
and improvement of programme performance.
In particular the role of local actors can hardly
be grasped by quantitative indicators alone, but has
to be addressed by assessing processes of social
innovation. This shift in the evaluation focus underpins
the need to take account of regional implementation
specificities and processes of social innovation as
decisive elements for programme performance.
Customer Relationship Management : Concept, Strategy, and Tools -3/E
Customer relationship management
(CRM) as a strategy and as a technology
has gone through an amazing evolutionary
journey. After the initial technological
approaches, this process has matured considerably – both from a conceptual and
from an applications point of view. Of
course this evolution continues, especially
in the light of the digital transformation.
Today, CRM refers to a strategy, a set of
tactics, and a technology that has become
indispensable in the modern economy.
Based on both authors’ rich academic and
managerial experience, this book gives a
unified treatment of the strategic and
tactical aspects of customer relationship
management as we know it today. It
stresses developing an understanding of
economic customer value as the guiding
concept for marketing decisions. The goal
of this book is to be a comprehensive and
up-to-date learning companion for
advanced undergraduate students, master
students, and executives who want a
detailed and conceptually sound insight
into the field of CRM
Graphs behind data: A network-based approach to model different scenarios
openAl giorno d’oggi, i contesti che possono beneficiare di tecniche di estrazione della conoscenza a partire dai dati grezzi sono aumentati drasticamente. Di conseguenza, la definizione di modelli capaci di rappresentare e gestire dati altamente eterogenei è un argomento di ricerca molto dibattuto in letteratura. In questa tesi, proponiamo una soluzione per affrontare tale problema. In particolare, riteniamo che la teoria dei grafi, e più nello specifico le reti complesse, insieme ai suoi concetti ed approcci, possano rappresentare una valida soluzione. Infatti, noi crediamo che le reti complesse possano costituire un modello unico ed unificante per rappresentare e gestire dati altamente eterogenei. Sulla base di questa premessa, mostriamo come gli stessi concetti ed approcci abbiano la potenzialità di affrontare con successo molti problemi aperti in diversi contesti. Nowadays, the amount and variety of scenarios that can benefit from techniques for extracting and managing knowledge from raw data have dramatically increased. As a result, the search for models capable of ensuring the representation and management of highly heterogeneous data is a hot topic in the data science literature. In this thesis, we aim to propose a solution to address this issue. In particular, we believe that graphs, and more specifically complex networks, as well as the concepts and approaches associated with them, can represent a solution to the problem mentioned above. In fact, we believe that they can be a unique and unifying model to uniformly represent and handle extremely heterogeneous data. Based on this premise, we show how the same concepts and/or approach has the potential to address different open issues in different contexts. INGEGNERIA DELL'INFORMAZIONEopenVirgili, Luc
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