The impact of Corporate Social Responsibility (CSR) policies on perceptions and behavioral intension of Greek consumers

During the last five years Greece has witnessed the exposure of an unprecedented number of corporate related events that had a significant impact on the public opinion (huge financial scandals, various corruption accusations, etc). These events dramatically increased the negative perception of consumers towards large companies operating in Greece. Corporate Social Responsibility (CSR) may be considered as an effective initiative that protects and strengthens the image and reputation of implementing companies, especially at a time that their status has been severely damaged by numerous distressing reports. The World Business Council for Sustainable Development (2000) defines CSR as a business commitment that supports sustainable economic development and, at the same time, contributes to the quality of life of employees, their families, the local community and society in general. Companies that implement CSR try to establish a positive business reputation and enhance the corporate brand name by taking actions that lead in the development of a competitive advantage, while at the same time contribute to the demands of various third parties. These companies shift from solely focusing on profits and tend to include financial, environmental and social goals in their core business strategies. Therefore, many researchers argue that the CSR policy is an activity mutually beneficial for both the business and society. However, several doubts about the effectiveness of these policies are being expressed. The purpose of the present study is to measure the perceptions of consumers about Greek Large Companies (GLC) and examine the influence of the implementation of CSR policies on consumers’ perception and consumers’ behavioral intention. The results of the quantitative research (N=454) highlighted the negative perceptions of Greeks towards GLC but, at the same time, revealed the statistically significant positive effect of CSR policies on consumers’ perceptions and behavioral intention.Corporate Social Responsibility, CSR, consumer’s perceptions, behavioral intention, Greece

A Memory Augmented Architecture for Continuous Speaker Identification in Meetings

We introduce and analyze a novel approach to the problem of speaker identification in multi-party recorded meetings. Given a speech segment and a set of available candidate profiles, we propose a novel data-driven way to model the distance relations between them, aiming at identifying the speaker label corresponding to that segment. To achieve this we employ a recurrent, memory-based architecture, since this class of neural networks has been shown to yield advanced performance in problems requiring relational reasoning. The proposed encoding of distance relations is shown to outperform traditional distance metrics, such as the cosine distance. Additional improvements are reported when the temporal continuity of the audio signals and the speaker changes is modeled in. In this paper, we have evaluated our method in two different tasks, i.e. scripted and real-world business meeting scenarios, where we report a relative reduction in speaker error rate of 39.28% and 51.84%, respectively, compared to the baseline.Comment: Submitted to ICASSP 202

Evaluation of e-banking dimensions by Greek customers

The use of electronic banking is increased rapidly worldwide. However, the percentage of Greek e-banking users, even if it has increased, is still very low. The adoption of e-banking depends on some factors which are connected with the services that the banks offer and the satisfaction from these factors influences, the overall satisfaction. The aim of this study was the exploration of the perception of Greek e-banking users about the factors affecting the satisfaction from the use of e-banking and moreover the influence of their experiences in the perception’s formation. In order to achieve the aims of this study a research was realized, using a structured questionnaire, in 354 users of e-banking. The results show that Greek customers are quite satisfied from the e-banking dimensions and moreover the dimensions that mostly affect the overall satisfaction are “trust” and “convenience/ usefulness”.peer-reviewe

Demonstrating Cognition by Task Execution and Motion Planning with different algorithms for Manipulation

In this Thesis we demonstrate the whole path until the manipulation and the planning of the Baxter Robot. We start by analyzing the kinematic analysis of a six degrees of freedom robot. We build our analysis starting from the Denavit-Hartenberg method. We proceed with the kinematic equations of the robot and with the inverse kinematics as well as with a kinematic simulation of its movement with matlab. In order to reach our final goal we continue with the kinematic and dynamic analysis of the Baxter robot. We again state the Denavit-Hartenberg matrix, but this time we continue by building the dynamic model of the Baxter robot through the Euler-Lagrange equations. Moving on, we explore planning algorithms. The knowledge of which will help us in order to finally be able to formulate our path planner for the Baxter robot. We experiment ourselves by implementing four planning algorithms in different path planning problems. We construct the RRT and the RRT* algorithms in Python and we process them in different planning problems. Moving on, we also implement a planning problem in which Q-Learning and Sarsa algorithms are being used. We demonstrate how those two planning and learning algorithms work in our specified problem and we compare our results. Having knowledge on dynamic and kinematic robotic analysis and planning and motion planning algorithms we then experiment ourselves with the Baxter simulator on Gazebo. Also we plan the Baxter robot with Moveit!, getting familiar with the use of ROS as well as with the software. We add obstacles in our world and we plan our Baxter robot measuring its speed. We finally build a different plan algorithm RRT+ by focusing on searching for a secure and realizable path plan starting from the lower dimension space and then adding degrees of freedom to our Baxter robot. Concluding, we have built the desired steps for someone in order to build up the required knowledge to deal with robots and artificial intelligence planning

Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels

Many existing FL methods assume clients with fully-labeled data, while in realistic settings, clients have limited labels due to the expensive and laborious process of labeling. Limited labeled local data of the clients often leads to their local model having poor generalization abilities to their larger unlabeled local data, such as having class-distribution mismatch with the unlabeled data. As a result, clients may instead look to benefit from the global model trained across clients to leverage their unlabeled data, but this also becomes difficult due to data heterogeneity across clients. In our work, we propose FedLabel where clients selectively choose the local or global model to pseudo-label their unlabeled data depending on which is more of an expert of the data. We further utilize both the local and global models' knowledge via global-local consistency regularization which minimizes the divergence between the two models' outputs when they have identical pseudo-labels for the unlabeled data. Unlike other semi-supervised FL baselines, our method does not require additional experts other than the local or global model, nor require additional parameters to be communicated. We also do not assume any server-labeled data or fully labeled clients. For both cross-device and cross-silo settings, we show that FedLabel outperforms other semi-supervised FL baselines by $8$-$24\%$, and even outperforms standard fully supervised FL baselines ($100\%$ labeled data) with only $5$-$20\%$ of labeled data.Comment: To appear in the proceedings of ICCV 202