No abstract

E-commerce has been increasingly applied as it promotes economic growth by enabling online shops to compete within a global market scenario. There are critical success factors that permit to distinguish a good business on the Internet and this knowledge may allow reaching an important competitive advantage for business sustainability. As many disciplines are involved, when determining critical success factors, ecommerce requires an effective coordination and integration in a collaborative way. In e-commerce, as well as in any other ecosystem, the breaking down of some integrating elements may provoke a collapse on the whole system. The various stakeholders involved in a given business should, therefore, be involved and work together to achieve a high-quality product that fully satisfies the end customer's needs and wishes. To meet the above requirement, this paper proposes a multi-perspective critical success factors (MPCSF) model for online shopping.

E-commerce promotes economic growth by enabling online shops to compete within a global market scenario. There are critical success factors that permit to distinguish a good business on the Internet and this knowledge may allow reaching an important competitive advantage for business sustainability. As many disciplines are involved, when determining critical success factors, e-commerce requires an effective coordination and integration in a collaborative way. In e-commerce, as well as in any other ecosystem, the breaking down of some integrating elements may provoke a collapse on the whole system. The various stakeholders involved in a given business should, therefore, be involved and work together to achieve a high quality product that fully satisfies the end customer's needs and wishes. To meet the above requirement, this paper proposes a multi-perspective critical success factors (MPCSF) model for online shopping.

In this paper we propose a knowledge based system (KBS), based on smart objects and a data fusion model to support industrial management decision making applied to a clothes manufacturing enterprise. The management processes cover factory-production levels to higher decision-making levels. Therefore, the proposed KBS contributes to solving different kind of decision problems, including factory supervision, production planning and control, productivity management, real-time monitoring, and data acquisition and processing. The web access via different middleware devices and tools at different process levels, along with the use of integrated algorithms, decision methods, and smart objects, promote an optimized use of knowledge and resources. In this paper the proposed KBS is introduced and an example of its use is illustrated with an example of a clothes manufacturing resources selection, using the embedded dynamic multi-criteria fusion model.

Along the last years, electrical energy distribution companies have already done many investments in order to identify and calculate energy losses along a distribution network. Although these big efforts, most approaches for clearly identifying and solving the related problems still remain rather inefficient. The accurate identification and the precise calculation of electricity losses enables the clear specification of the critical points and segments in the networks and, consequently, the effective prioritization of actions and interventions in order to reduce those electricity losses and problems. Moreover, the work already performed on this issue, the existing approaches focus mainly on empirical and probabilistic data. Hence, there is still a clear gap between real information and the considered one, which tends to be poor and imprecise. Due to this reality and the lack of appropriate software applications, in this paper we propose a web platform for the management of the whole network of electrical energy distribution, from medium voltage (MV) down to low voltage (LV), including billing on the transformation centers (TCs), electricity losses calculation and proposals for solving actions, by means of a fuzzy decision-making model.