No abstract

Cloud computing hastens technology driven innovation by taking advantage of the speed, the cost-effectiveness, the efficiency and the security that such applications offer. By using cloud computing, public organizations can exploit the economies of scale and innovate both efficiency and rapidly. The present study focuses on the factors influencing the adoption of a new technological application within the procedures of change management. It examines the willingness to adopt cloud computing for the case of administrative employees in a higher education institute working environment. A prediction model explores a Ubiquitous cloud computing adoption system (USAS), utilizing the theory of technology acceptance model (TAM) and resulting that end users are welcoming the adoption of the cloud computing. Policy makers should move towards empowering the stakeholders with e-skills to stimulate technology driven innovation, resulting in improvements in effectiveness and efficiency, in the creation of new jobs and in the promotion of sustainable development practices.

Willingness to invest in renewable energy sources (RES) is predictable under data mining classification methods. Data was collected from the area of Evia in Greece via a questionnaire survey by using a sample of 360 respondents. The questions focused on the respondents’ perceptions and offered benefits for wind energy, solar photovoltaics (PVs), small hydro parks and biomass investments. The classification algorithms of Bayesian Network classifier, Logistic Regression, Support Vector Machine (SVM), C4.5, k-Nearest Neighbors (k-NN) and Long Short Term Memory (LSTM) were used. The Bayesian Network classifier was the best method, with a prediction accuracy of 0.7942. The most important variables for the prediction of willingness to invest were the level of information, the level of acceptance and the contribution to sustainable development. Future studies should include data on state incentives and their impact on willingness to invest.

The aim of this article is to present data concerning customers’ satisfaction with the 4 systemic banks operating in Greece. Today, the market share of these banks is over 95%, as the economic crisis of 2010 has led to structural changes in the banking industry of the country. At the same time, the conditions created by the COVID-19 pandemic will potentially lead to additional changes such as a more intensive use of alternative networks. To collect the research data, 5,018 questionnaires have been responded by retail customers of the 4 systemic banks operating in Greece during the period between June 2017 and June 2019. The criteria used to determine customers’ satisfaction with the 4 systemic banks of banks concern products and services, branch network, staff and customer service. Τhe collected data have been analyzed using the Muticriteria Satisfaction Analysis (MUSA) method. The results of the MUSA method provide several evidence that can be taken into account during the strategic development process of any organization including banks.

As the world progresses, management of change is seen as an opportunity for organizations to improve their competitive edge, their profits and productivity. Companies around the world become more specialised and focused on their core competencies and rely largely on niche markets. On the other hand, it is noteworthy that management change is process that undoubtedly generates a perceived efficacy among workforce. This fact may signify the generation of key-organizational behavior indicators, such as job satisfaction. This study is theoretically exploring the relationship between the perceived efficacy of a management change process and job satisfaction.