The Relationship between Social Responsibility and Business Performance: An Analysis of the Agri-Food Sector of Southeast Spain

This study aims to contribute to the existing debate on the impact of corporate social responsibility (CSR) orientation on different measures of business performance through the proposal of a conceptual model. Drawing on stakeholder theory, we conceptualize CSR as a broad and multidimensional construct with seven dimensions: employees, partners, customers, farmers, environment, community, and competition. We also extend the concept of business performance, which includes tangible variables, namely financial performance (FP) and export performance (EXP), as well as intangible variables, namely image and reputation (IR) and the satisfaction of relevant stakeholders (SS). The research context of this study is the agri-food sector in southeastern Spain. This sector has been the focus of attention of numerous researchers due to the relevance that social and environmental aspects have had in its development. To test the proposed model, the partial least-squares technique (PLS-SEM) was applied to data collected by means of a survey from a sample of 107 companies, which represent 81.4% of the turnover of the sector analyzed. The results show that CSR has a positive effect on financial performance, improves the volume and performance of exports, positively affects the corporate image and reputation, and increases the level of satisfaction of relevant stakeholders. Further research should examine the model from the perceptions of other stakeholders (e.g., customers, employees, and suppliers), using a longitudinal research design and exploring other contexts

Adding X-security to Carrel: security for agent-based healthcare applications

The high growth of Multi-Agent Systems (MAS) in Open Networks with initiatives such as Agentcities1 requires development in many different areas such as scalable and secure agent platforms, location services, directory services, and systems management. In our case we have focused our effort on security for agent systems. The driving force of this paper is provide a practical vision of how security mechanisms could be introduced for multi-agent applications. Our case study for this experiment is Carrel [9]: an Agent-based application in the Organ and Tissue transplant domain. The selection of this application is due to its characteristics as a real scenario and use of high-risk data for example, a study of the 21 most visited health-related web sites on the Internet discovered that personal information provided at many of the sites was being inadvertently leaked for unauthorized persons. These factors indicate to us that Carrel would be a suitable environment in order to test existing security safeguards. Furthermore, we believe that the experience gathered will be useful for other MAS. In order to achieve our purpose we describe the design, architecture and implementation of security elements on MAS for the Carrel System.Postprint (published version

SOA4 All Integrated Ranking: a Preference-Based, Holistic Implementation

There exist many available service ranking implementations, each one providing ad hoc preference models that offer different levels of expressiveness. Consequently, applying a single implementation to a particular scenario constrains the user to define preferences based on the underlying formalisms. Furthermore, preferences from different ranking implementation’s model cannot be combined in general, due to interoperability issues. in this article we present an integrated ranking implementation that enables the combination of three different ranking implementations developed within the EU FP7 SOA4All project. Our solution has been developed using PURI, a Preference-based Universal Ranking Integration framework that is based on a common, holistic preference model that allows to exploit synergies from the integrated ranking implementations, offering a single user interface to define preferences that acts as a façade to the integrated ranking implementation

Improving Semantic Web Services Discovery Using SPARQL-Based Repository Filtering

Semantic Web Services discovery is commonly a heavyweight task, which has scalability issues when the number of services or the ontology complexity increase, because most approaches are based on Description Logics reasoning. As a higher number of services becomes available, there is a need for solutions that improve discovery performance. Our proposal tackles this scalability problem by adding a preprocessing stage based on two SPARQL queries that filter service repositories, discarding service descriptions that do not refer to any functionality or non-functional aspect requested by the user before the actual discovery takes place. This approach fairly reduces the search space for discovery mechanisms, consequently improving the overall performance of this task. Furthermore, this particular solution does not provide yet another discovery mechanism, but it is easily applicable to any of the existing ones, as our prototype evaluation shows. Moreover, proposed queries are automatically generated from service requests, transparently to the user. In order to validate our proposal, this article showcases an application to the OWL-S ontology, in addition to a comprehensive performance analysis that we carried out in order to test and compare the results obtained from proposed filters and current discovery approaches, discussing the benefits of our proposal

On User Preferences and Utility Functions in Selection: A Semantic Approach

Discovery tasks in the context of Semantic Web Services are generally performed using Description Logics. However, this formalism is not suited when non-functional, numerical parameters are involved in the discovery process. Furthermore, in selection tasks, where an optimization algorithm is needed, DLs are not capable of computing the optimum. Although there are DLs extensions that can handle numerical parameters, they bring decidability problems. Other solutions, as hybrid approaches which use DLs in functional discovery and other formalisms in non-functional selection, do not provide a semantic framework to describe user preferences based on non-functional properties. In this work, we propose to semantically describe user preferences, so they can be used to perform selection within a hybrid solution. By using semantically described utility functions in order to define user preferences, our proposal enables interoperability between service offers and demands, while providing a high level of expressiveness in these preferences and including them within SWS descriptions.Comisión Interministerial de Ciencia y Tecnología TIN2006-0047

A Service Ranker Based on Logic Rules Evaluation and Constraint Programming

Ranking of Semantic Web Services is usually performed based on user preferences descriptions. These descriptions are expressed in terms of an underlying logical formalism, which limits their expressiveness. Thus, there are some kind of descriptions, such as utility functions, that cannot be handled by reasoners currently being used to perform Semantic Web Services tasks, though utility functions provide a higher level of expressiveness. in this work, we present a hybrid solution to allow the introduction of utility functions in user preferences descriptions, using both Logic Programming rules evaluation and Constraint Programming to perform the ranking process. This proposal is based on the Web Service Modeling Ontology, extending it with a highly expressive framework to specify user preferences, and enabling the integration of different engines to perform the ranking process

Effects of Mergers and Acquisitions on Shareholder Wealth: Event Study for Latin American Airlines

This study analyzes the effectof changes in corporate controlon the way shareholdersbenefit from the announcements of selling and buying airlines, thus contributing to the literature on mergers and acquisitions (M&As) in emerging markets. Using a methodologyof event study, including GARCH and OLS models, we find evidence that some selling companies obtain abnormal returns that are statisticallysignificant after the announcement of the M&A. However, when the merger is not strategic, the companies present statisticallysignificant negative abnormal returns. The resultsare not conclusive when analyzing the effecton the valueof the buying companies

Integrating Semantic Web Services Ranking Mechanisms Using a Common Preference Model

Service ranking has been long-acknowledged to play a fundamental role in helping users to select the best o erings among services retrieved from a search request. There exist many ranking mechanisms, each one providing ad hoc preference models that o er di erent levels of expressiveness. Consequently, applying a single mechanism to a particular scenario constrains the user to de ne preferences based on that mechanism's facilities. Furthermore, a more exible solution that uses several independent mechanisms will face interoperability issues because of the di erences between preference models provided by each ranking mechanism. In order to overcome these issues, we propose a Preference- based Universal Ranking Integration (PURI) framework that enables the combination of several ranking mechanisms using a common, holistic preference model. Using PURI, di erent ranking mechanisms are seamlessly and transparently integrated, o ering a single fa cade to de ne preferences using highly expressive facilities that are not only decoupled from the concrete mechanisms that perform the ranking process, but also allow to exploit synergies from the combination of integrated mechanisms. We also thoroughly present a particular application scenario in the SOA4All EU project and evaluate the bene ts and applicability of PURI in further domains

QoS-Aware Semantic Service Selection: An Optimization Problem

In order to select the best suited service among a set of discovered services, with respect to QOS parameters, a user have to state his or her preferences, so services can be ranked according to these QOS parameters. Current Se- mantic Web Services ontologies do not support the defini- tion of QOS-aware user preferences, though there are some proposals that extend those ontologies to allow selection based on those preferences. However, their selection algo- rithms are very coupled with user preferences descriptions, which are defined without semantics or at a different seman- tic level than service functionality. In this work, we present a service selection framework that transforms user prefer- ences into an optimization problem where the best service is selected. This framework is based on an ontology that conceptualizes these user preferences. Thus, we use a very expressive solution decoupled with the concrete selection technique by using XSL transformations, while describing QOS-aware user preferences at the same semantic level of functional preferences.Comisión Interministerial de Ciencia y Tecnología TIN2006-00472Junta de Andalucía TIC-253