Increasing the sustainability of a system can be achieved by evaluating the system, identifying the issues and their root cause and solving them. Performance evaluation translates into key performance indicators (KPIs) with a high impact on increasing overall efficacy and efficiency. As the pool of KPIs has increased over time in the context of evaluating the supply chain management (SCM) system’s performance and assessing, communicating and managing its risks, a mathematical model based on neural networks has been developed. The SCM system has been structured into subsystems with the most relevant KPIs for set subsystems and their most important contributions on the increase in the overall SCM system performance and sustainability. As a result of the performed research based on the interview method, the five most relevant KPIs of each SCM subsystem and the most relevant problems are underlined. The main goal of this paper is to develop a performance evaluation model that links specific problems with the most relevant KPIs for every subsystem of the supply chain management. This paper demonstrates that by using data mining, the relationship between certain problems that appear in the supply chain management of every company and specific KPIs can be identified. The paper concludes with a graphical user interface (GUI) based on neural networks using the multilayer perceptron artificial intelligence algorithm where the most trustworthy KPIs for each selected problem can be predicted. This aspect provides a highly innovative contribution in solving supply chain management problems provided by organizations by allowing them to holistically track, communicate, analyze and improve the SCM system and ensure overall system sustainability.

International projects have helped organizations around the world to better adapt to the new environmental conditions in which they operate, driven by the phenomenon of globalization. Electronic communication and information tools have enabled the creation of international virtual project teams (IVPTs), allowing team members to collaborate regardless of their geographic location or cultural, historical, socio-political, and educational differences. However, such an environment characterized by diversity will be productive only if the project team managers acknowledge and understand the behavior of influence factors comprised by the virtual environment, developing, accordingly, strategies that support team performance. In order to analyze the factors that influence IVPT performance, we used a C5.0 algorithm on the dataset through IBM SPSS Modeler software. Data collection was performed through an online survey, conducted within 107 IVPT members and managers, in order to answer the third question of the research. The predictive model created by the data mining algorithm revealed that the most important fields underlying the decision tree building were the cognitive skills training programs, team culture, and selection of IVPT members based on the characterisics of their national cultures. These results demonstrate the hypothesis that culture represents one of the most important factors influencing team performance.

MATEC Web of Conferences, open access proceedings in Materials science, Engineering and Chemistry

The relationship between the degree of taxation, the activity of firms and the performance measured by the ability to achieve positive results and to ensure a financial equilibrium has been an important issue in the debate in a great deal of research, but in most of them, the analyses were reported according to a set of factors (inclusive the fiscal degree). This paper comprises an empirical investigation to identify the effects of the degree of taxation on financial stability and the balance of enterprises. An analysis of the degree of taxation and of the economic growth rate in Romania was made in the first part, and, after that, empirical analyzes were conducted on how the volume of taxes, the capital structure and other indicators influences the level of value added as well as the volume of fiscal pressure and the duration of payment of tax liabilities. Using data on the level of macroeconomic taxation, as well as information on financial equilibrium indicators at the level of some representative companies in the field of rubber and plastic processing listed on the stock exchange, a model of the existing relationships between a series of indicators related to financial equilibrium and economic growth rate, fiscal pressure and profitability was produced, using statistical analyses based upon multiple regressions and simulations in SPSS software. The main conclusions show that taxes and fees influence the financial positions of firms by changes in the volume and structure of the capital used, the level of profit/loss, as well as financial equilibrium, at the level of solvency and liquidity. Also, the results extend the understanding of the importance the tax administration in creating added value, ensuring financial equilibrium and good performance in the context of the sustainable development of companies.

This paper focuses on the suppliers’ evaluation and selection and aims to develop a criterial model of suppliers’ evaluation as an innovative method for engineering and business education. This new method comes with the purpose of organisational supply chain management performance growth, by improving the entire supply chain system and engineering process, and bringing contribution to the specialty literature in this field. The research methodology is based on qualitative research. The bibliographic research from various secondary sources is used, such as diverse books, scientific articles, reports and information material. In order to achieve a high performance in an organisation it is necessary to monitor and control the procurement process. Certain gaps have been identified in identifying a supplier rating and selection system based on both logistical, financial, price or quality aspects. As an own contribution, this paper proposes a criterial model of evaluating and selecting suppliers, based on specific aspects related to the product, services, delivery and to the financial situation. The motivation of choosing this model is found in its capacity of noticing the negative aspects regarding the relationship between an organisation and its suppliers and finding out the improvement aspects, with a high impact on the engineering process’ and supply chain management’s improvement. The model offers the possibility to benchmark the suppliers, aspect which favours the potential collaboration with future suppliers.

This study aims to appraise teaching staff’s acceptance with organizational trust, culture, process and elements, followed by an attempt to construct a model to predict change acceptance. This study employed online survey questionnaires for data collection. Participants in this research are teaching staff experiencing the adoption of new technology change, Blended Learning, at two public higher education institutions in Cambodia. The study found that majority of teaching staff expressed their support towards the change program, yet not all of them had adopted such changes in their work. The analyses of these six-paired variables-change acceptance, trust, task and relationship cultures, change process, strategy and technology-confirm positive correlations. There is also sufficient evidence proving that change acceptance can be predicted from these early dimensions, and relationship culture is found to be a significant predictor.