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In the current competitive environment, each company faces a number of challenges: quick response to customers’ demands, high quality of products or services, customers’ satisfaction, reliable delivery dates, high efficiency, and others. As a result, during the last five years many firms have proceeded to the adoption of enterprise resource planning (ERP) solutions. ERP is a packaged software system, which enables the integration of operations, business processes and functions, through common data‐processing and communications protocols. However, the majority, if not all, of these systems do not support the production scheduling process that is of crucial importance in today’s manufacturing and service industries. In this paper, the authors propose a knowledge‐based system for production‐scheduling that could be incorporated as a custom module in an ERP system. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.

Within the last decade many projects have been implemented in order to provide technical assistance (TA) to countries, which have initiated their transition from centrally planned to market economies (mainly countries of Central and Eastern Europe being previously under the Soviet regime). The monitoring and evaluation exercise aims at assisting these TA projects in achieving their objectives, by providing management information on the projects’ implementation, so that structured management decisions can be taken, if and when needed. In this framework, the necessity for creation of an overall M&E database system emerged. The IMES was developed for the needs of the European commission (DGLA) and its main objective was to improve the Management Reporting on Tacis progress and results, by extracting relevant information on projects’ performance from the monitoring and evaluation reports and by producing overall statistics at NIS (New Independent States) level.

Presents the NUMASS Web‐based system, which was developed for the needs of the European Commission (designed to be used mainly by AIDCO‐A5). Its main objective is to improve the management and monitoring of Tacis Nuclear Safety Programme, by showing in a graphical way the progress of projects/works and prompting for corrective actions.

Within the last decade many projects have been implemented in order to provide technical assistance (TA) to countries which have initiated their transition from centrally planned to market economies (mainly countries of Eastern Europe being previously under the Soviet regime). The “monitoring and evaluation” function (M&E) helps in seeing whether each TA project is being developed as per its design and achieves its objectives by providing management information on the project’s implementation. In this framework, the necessity for the creation of an overall M&E database system emerged, with the main objective to improve not only the management of TA projects but also the design and planning of future TA projects.

Planning and scheduling are forms of decision making, which play a crucial role in manufacturing as well as in service industries. In the current competitive environment, effective sequencing and scheduling has become a necessity for survival in the marketplace. A great challenge for today’s companies is not only how to adapt to this changing, competitive business environment but also how to draw a competitive advantage from the way in which they choose to do so. Intelligent solutions, based on expert systems, to solve problems in the field of production planning and scheduling are becoming more and more widespread nowadays. Proposes an expert system, which uses the prevailing conditions in the industrial environment in order to select and “fire” dynamically the most appropriate scheduling algorithm from a library of many candidate algorithms.

It is common knowledge that during the last decade markets have become extremely competitive with product variety increasing continuously and product life cycles shortening. Many manufacturing companies, which hitherto satisfied their customers while operating specific production systems, were recently obliged to reconsider because of the potential superiority of other “manufacturing philosophies”. In the literature, we meet a great variety of production systems and manufacturing philosophies, while, on the other side, in industry we usually find different combinations of “primary” productions systems. In this paper, we present the existing “state‐of‐the‐art” theoretical and experiential knowledge about productions systems, as well as describe their basic characteristics in a useful, exact and comprehensive way for practitioners and software houses who want to have a knowledge base for further research and practical implementation in the wider field of production management, planning and scheduling.

In this paper we consider the use of ontologies as the basis for structuring and simplifying the process of constructing real‐time problem‐solving tools, focusing specifically on the task of production scheduling. In spite of the commonality in production scheduling system requirements and design, different scheduling environments invariably present different challenges (e.g. different constraints, different objectives, different domain structure, etc.). The proposed methodology for building ontologies used for production scheduling systems represents a synthesis of extensive work in developing constraint‐based scheduling models for a wide range of applications in manufacturing and production planning. Since the effective modeling is one of the most important and difficult steps in the development of reliable information systems, and taking into consideration the fact that the general problem of the production scheduling in the industries is very difficult and still unsolved, one can easily estimate the merit of this methodology.

In the context of today's knowledge economy, development policies that are mainly based on knowledge as a primary source of wealth and added‐value are increasingly adopted by cities and countries. This tendency is becoming much more common due to the global financial crisis. Thus, the knowledge‐based development field has been in a state of important progress during the last decade. This paper seeks to discuss and highlight the major issues of knowledge‐based development. By doing so the paper aims to present an agenda for future research directions for the present decade of 2010‐2020.

The paper presents an agenda for future research by co‐instantaneously presenting the status in relation to the major pending issues of the knowledge‐based development field. This is accomplished through a wide‐scope literature review and qualitative scoring of knowledge‐based development (KBD) categories.

The main finding is that research is needed in four main directions: development of holistic and unified approaches for the practical formulation of citizen‐centric knowledge‐based development strategies; knowledge‐based urban planning; knowledge‐based development assessment and metrics; practical aspects of implementation of knowledge‐based development approaches.

Research in the paper is based on a wide literature review of the most important and added‐value available resources in the KBD field and in qualitative scoring of research categories. Use of empirical components such as citation analysis, field surveys, knowledge network analysis as well as for a specific approach regarding the scoring system would be needed in future research.

The discussion and issues presented in the paper should be of value not only to researchers and practitioners but also to cities and countries willing to design efficient and effective knowledge‐based development strategies.

Knowledge management (KM) has recently received considerable attention in the computer information systems community and is continuously gaining interest by industry, enterprises and government. Decision support and KM processes are interdependent activities in many organizations. In all cases, decision makers always combine different types of data and knowledge available in various forms in the organization. One of the key – but also criticized – building blocks for advancing this field of knowledge management and consequently supporting the decision making is artificial intelligence (AI). In this framework, this paper aims to improve understanding of AI towards knowledge management. It examines and discusses both the potential and the limitations of basic AI technologies in terms of their capability to support the KM process and shares thoughts and estimations on further research on the development of the next generation decision support environments.

The concept of knowledge cities (KCs) is particularly advantageous for any contemporary city. Many cities globally claim themselves as being already KCs, while other cities have elaborated strategic plans in order to be transformed into KCs. The examination of their approaches reveals that these initiatives are fragmented and there is not a unified and coherent methodological approach. The purpose of this paper is to present the basic elements of a methodological approach for the integrated development of a KC.

The examination and analysis of many cities' approaches, on a previous research work, have permitted one to identify an emerging pattern of successful KCs' main characteristics and features. These characteristics served as the basis in order to develop a methodological approach for the development of a KC.

The paper presents the basic elements of a methodological approach, named KnowCis (knowledge cities), which consists of five main phases.

The concept of KCs is very broad and consequently the purpose of the proposed approach is to incorporate all the related aspects. A suggestion for future research is the enhancement of the approach in order to incorporate additional aspects of a city's life.

The KnowCis approach is a useful tool for any city that intends to be developed as a KC. At this stage there is an ongoing collaboration with a Greek city for its pilot application.

The approach presented in this paper is unified and it can be easily adapted in order to comply with the particular characteristics of each city.