Bayesian network-based risk prediction in virtual organizations

To support and increase the success rate of collaboration in Virtual Organizations (VOs), usually formed within Virtual organizations Breeding Environments (VBEs), their operation stage and performance of their tasks must be continuously monitored and supervised. A task in the VO is either planned to be performed by an individual partner or jointly by a group of partners, and typically consists of several sub-tasks defining the day-to-day activities of its involved partners. However, VOs are dynamic and therefore detailed activities related to sub-tasks are defined gradually during their operation phase. In this paper, as the base for discovery of potential task failures, past performance and record of previous sub-tasks’ fulfillment of each partner (so-called agent) is considered for appraisal of its trustworthiness. Furthermore, the communication characteristic of the agent and its current workload in all its involved VOs within the VBE are also considered as input for measuring its potential probability of failure on currently assigned sub-tasks. For tasks that involve several partners, a Bayesian network is created during the VO’s operation phase, and used for measuring their failure probabilities. These two potential risk measurements in VOs enable their coordinators to appropriately identify the weak points in their planning of upcoming VO activities, as well as assisting them with advice on how to intervene and change the situation

Green virtual enterprise breeding environments bag of assets management: A contribution to the sharing economy

Green Virtual Enterprise Breeding Environments (GVBEs) are longterm strategic alliances of green enterprises and their related support institutions aimed at offering the necessary conditions to efficiently promote and establish common working and sharing principles with the intention of creating sustainable (shared) value in a collaborative way. The Sharing Economy (SE) is founded on the principle of maximising the utility of assets and other shareable resources by means of renting, lending, swapping, bartering and giving them away in order to avoid their idle existence, and is currently being facilitated by emerging collaborative business ICT infrastructures in the marketplace and society. The SE provides the ability to GVBE members to unlock the untapped social, economic and environmental value of their underutilised assets and other shareable resources towards higher resource efficiency. This paper explores the enabling role of the GVBE bag of assets as a virtual and physical warehouse, including collaborative procurement and shareable assets management strategies, in order to facilitate the sharing of tangible and intangible resources between GVBE members. The GVBE bag of assets is put forward as a novel internal sustainable business model, based on a conceptual framework, taking advantage of idle assets and other shareable resources within the breeding environment in order to save costs and generate new revenue streams (economic), make efficient use of resources (environment) and create deeper social connections – trust – among member enterprises (social)

Data scientist : the engineer of the future

Although our capabilities to store and process data have been increasing exponentially since the 1960s, suddenly many organizations realize that survival is not possible without exploiting available data intelligently. Out of the blue, "Big Data" has become a topic in board-level discussions. The abundance of data will change many jobs across all industries. Moreover, also scientific research is becoming more data-driven. Therefore, we reflect on the emerging data science discipline. Just like computer science emerged as a new discipline from mathematics when computers became abundantly available, we now see the birth of data science as a new discipline driven by the torrents of data available today. We believe that the data scientist will be the engineer of the future. Therefore, Eindhoven University of Technology (TU/e) established the Data Science Center Eindhoven (DSC/e). This article discusses the data science discipline and motivates its importance. Keywords: Data science; Big data; Process mining; Data mining; Visual analytics; Internet of thing

Solving the earthquake disaster shelter location-allocation problem using optimization heuristics

Earthquakes can cause significant disruption and devastation to populations of communities. Thus, in the event of an earthquake, it is necessary to have the right number of disaster shelters, with the appropriate capacity, in the right location in order to accommodate local communities. Mathematical models, allied with suitable optimization algorithms, have been used to determine the locations at which to construct disaster shelters and allocate the population to them. This paper compares the use of two optimization algorithms, namely a genetic algorithm and a modified particle swarm optimization, both of which have advantages and disadvantages when solving the disaster shelter location-allocation problem

ECoNet platform for collaborative logistics and transport

The development of the Port Community System (PCS) concept, as a single access point to a port, offering integrated logistics and transport services, is a complex and challenging endeavour. Effective value creation in PCS requires the integration of stakeholder’s internal processes with the collaborative activities/ processes, under an open framework. The establishment of such community thus requires a well-founded collaborative framework to integrate and coordinate the diverse IT-systems of the participating stakeholders. These IT-systems, in most of the cases, were not designed and developed for a cooperation context, leading to a complex overpriced web of disconnected systems that are difficult to manage, maintain, and adapt to the fast evolution of technologies and collaboration models. In this context, an enhanced Enterprise Collaborative Network platform is presented and discussed as an approach to support PCS

Agent-based modelling and simulation for lecture theatre emergency evacuation

This paper presents an overview of ongoing research into the implementation of an agent-based model aimed at providing decision support for the layout design of lecture theatres and human behavioural management in emergency evacuation. The model enables the spatial layout of lecture theatres to be configured and incorporates agent behaviours at the basic movement and individual level. In terms of individual behaviours, agents can be competitive, cooperative, climb obstacles (e.g. seating and desks) and fall down. Two cases are investigated to evaluate the effects of different exit locations in lecture theatres and competitive behaviour of agents on evacuation efficiency in multiple scenarios