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PurposeIn 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.Design/methodology/approachThe 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.FindingsThe 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 limitations/implicationsResearch 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.Originality/valueThe 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.

PurposeTo survive in the global economy, SMEs have to improve their products, services and processes, exploiting their intellectual capital in a dynamic network of knowledge‐intensive relations inside and outside their borders. This paper aims to explore the rationales for the integration of knowledge management (KM) and ERP in SMEs and to present a conceptual model for their integration.Design/methodology/approachA wide range of academic and practitioner literature related to ICT and KM adoption from SMEs is reviewed. On the basis of this review and analysis, a conceptual model is designed.FindingsThe proposed model is regarded as an adaptable solution, where an SME with a traditional business structure uses existing IT applications and builds on them. Before applying the proposed model, SMEs should ensure that their KM initiatives fit into their organisational culture, or otherwise they should be prepared to change it.Research limitations/implicationsThe applicability of this model in an SME seeking to gain a competitive advantage needs to be explored. Practitioners should use the model in order to develop new platforms and extended ERP modules.Practical implicationsThe model can be used in any area of information and knowledge management.Originality/valueUsing the model, SMEs can achieve the integration of ERP and KM, which is proven to be a necessity for them in the knowledge economy.

PurposeKnowledge cities (KCs) are cities in which both the private and the public sectors value knowledge, nurture knowledge, spend money on supporting knowledge dissemination and discovery and harness knowledge to create products and services that add value and create wealth. Knowledge cities fall under a new area of academic research entitled knowledge‐based development (KBD), which brings together research in urban development and urban studies and planning with knowledge management and intellectual capital. The purpose of this paper is to advance the research in the KC area by exploring stakeholder knowledge partnerships in a knowledge city.Design/methodology/approachBased on their previous research, the authors' main discussion highlights the need for more effective local government and stakeholder knowledge partnerships to better support knowledge management (KM) initiatives in a KC and proposes a conceptual model, as a good research starting‐point, to assist local governments develop and capitalize on more effective knowledge‐based stakeholder partnerships.FindingsThe main issues related to local government‐stakeholder partnerships are discussed and several processes are analyzed that can facilitate more effective two‐way knowledge transfers between local government and stakeholders in a KC, which are fundamental for establishing successful knowledge partnerships.Research limitations/implicationsIt would be interesting and useful to deepen the analysis made by the authors and look for more fundamental reasons behind their observations.Originality/valueThe main advantage of this paper is that it proposes a simplified conceptual model for stakeholder knowledge partnerships in knowledge cities.

PurposeThe concept of knowledge cities (KCs) offers advantages to any urban region. Many cities globally claim themselves as being already KCs, while other cities have elaborated strategic plans in order to integrate this concept into their operational structures. The examination of their approaches reveals however that these initiatives are fragmented. The purpose of this paper is to present a multi‐dimensional and integrated decision support model for a KC's strategy formulation.Design/methodology/approachReference is made to a methodological approach (KnowCis) for the integrated development of a KC, consisting of five main phases and taking into account nine different dimensions. The strategy formulation phase is a particularly complex procedure for any authority (e.g. local government or city's development agency). The reasons for this complexity are related to the amplitude of the KC concept, to the variety of the factors to be considered as well as to the challenge for balancing the needs and interests of different target groups.FindingsThe proposed model consists of the following building blocks: identification of the appropriate actions (based on the KnowCis methodology), modeling of the city's current status as a KC (via the development of related indicators), assessment of actions' necessity (based on the indicators' outcomes and through the benchmarking of other successful KCs cases), selection of the most appropriate form for each proposed action (based on their efficiency during the last reference period) and, finally, prioritisation of the proposed actions (based on a multi‐criteria approach).Research limitations/implicationsThe main suggestion for future research is the development of an intelligent information system which will incorporate the building blocks of the proposed model.Originality/valueThe originality and value of the paper is that the proposed model can be a really helpful decision support tool for any city which is developing a knowledge‐based strategy.

PurposeThe purpose of this paper is to propose an approach for describing and discovering knowledge resources in distributed environments.Design/methodology/approachThe paper proposes a solution that includes a framework model and a technological infrastructure to achieve distributed knowledge discovery. It provides the solution based on a combination of research from knowledge management and distributed processing areas.FindingsThe paper finds a faceted ontology and three discrete models that best achieve distributed processing in terms of knowledge items and knowledge objects. By these mechanisms are provided to: represent knowledge in a generic manner that will unchain knowledge from tight links to specific contexts, purposes and audiences; discover and retrieve knowledge stored in distributed sources; interpret different knowledge representations to enable comprehension of knowledge on the recipient side and tackle the heterogeneity problem; and simplify and accelerate knowledge exchange in distributed environments.Research limitations/implicationsThe utilization of knowledge in distributed environments (intra‐ or inter‐organizational) presupposes the existence of a representation of knowledge in a commonly understandable manner. Knowledge resources are distributed in the web and databases in an unstructured manner.Practical implicationsThe paper can be used as the basic consensus and infrastructure for the development of a coherent, manageable semantic web. The three models should be addressed in terms of commercial applications.Originality/valueKnowledge management and distributed processing research fields are combined in order to provide a solution that best addresses the problem of distributed knowledge.

PurposeThe 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.Design/methodology/approachThe 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.FindingsThe paper presents the basic elements of a methodological approach, named KnowCis (knowledge cities), which consists of five main phases.Research limitations/implicationsThe 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.Practical implicationsThe 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.Originality/valueThe approach presented in this paper is unified and it can be easily adapted in order to comply with the particular characteristics of each city.

PurposeIn the new era of knowledge economy, knowledge and the processes to generate it and manage it are considered to be the most valuable assets of an organisation in the competitive business environment. Over the last years, intensive discussions have taken place about the importance of knowledge management for the whole of society, except for the business world. Today, there is a consensus among researcher and practitioner communities that the challenges facing modern societies call for development strategies that are knowledge‐based. Such strategies could enable humankind to pursue the vision of a global society in which all the basic human needs can be satisfied, while maintaining a healthy and physically attractive environment. However, general agreement has not yet been reached on which type of knowledge‐based development (KBD) strategy is the most advantageous and should be followed. This paper attempts, on the one side, through the study of current literature, to demonstrate the needs that should be fulfilled by KBD strategies and, on the other side, to justify why the relatively new concept of knowledge cities is the one that fully corresponds to these needs.Design/methodology/approachThe authors attempt to review and analyse in a coherent way the current trends regarding KBD policies as well as to examine the needs to be addressed by successful KBD strategies, based on a wide range of published works, including papers, books, reports and web sites.FindingsThe main finding is that there are many issues that contemporary KBD policies should address and that the new concept of knowledge cities fully corresponds to these needs.Research limitations/implicationsRecommended directions for further action research are presented.Originality/valueThe distinguishing feature of this study is that it shows that the concept of a knowledge city is the most appropriate and advantageous model for a KBD strategy, fully complying with and satisfying their needs.

Purpose – This paper aims to deal with the development of a risk management application for the modelling, optimal adaptation and implementation of an ERP system.Design/methodology/approach – This paper presented a risk management application for the modeling, optimal adaptation and implementation of an ERP system. The application was tested with the operations and capabilities of the ERP commercial package “SINGULAR Enterprise (SEn)” of the Greek Software House DELTA‐SINGULAR S.A.Findings – The functional result of this application was proved to support considerably the management of risk within the implementation of the ERP system.Originality/value – To the best knowledge of the authors there is no other current generic research in this technological field concerning small or medium‐sized enterprises. With the development of this application, the goals mentioned in the conclusions were achieved.

PurposeDuring the last 15 years, knowledge management (KM) has changed from one generation to the next through constant improvements and new perspectives. A myriad researchers have presented methodologies, frameworks, technologies and have discussed various KM theoretical and practical issues. However, KM still needs extensive development – it is in its infancy. This paper aims to explore the world of KM in a different way; to review the current status quo and analyze the main agreements and disagreements among researchers and practitioners in order to highlight the key issues which need to be further researched.Design/methodology/approachThe authors attempt to review and analyze in a coherent way the main agreements and disagreements among researchers and practitioners – in the field of KM – based on a wide range of published works, including papers, books, reports and web sites.FindingsBased on the key agreements among researchers and practitioners and having in mind the remaining disagreements, the third KM generation should proceed to further investigation of several KM issues and to further research.Research limitations/implicationsThe key issues highlighted here need to be researched further. Following on from the individual‐knowledge focus of the 1970s/1980s and the group‐knowledge focus of the 1990s/2000s, the third KM generation should: develop criteria for evaluating frameworks, methodologies and approaches, and systems for measuring knowledge, intellectual capital and other assets; include double‐loop learning; analyse investments and costs of KM Systems; use modern technologies for transfer of explicit knowledge; and apply KM to other areas of social life. There is also a need to clarify the meanings of differences between the various concepts discussed here.Originality/valueThe distinguishing feature of this study is that it emphasizes placing KM in a broader context of researchers/practitioners’ discussions so that the key issues can be better recognized and understood.

PurposeTo control and reduce the time and the cost of implementation and to achieve optimal adaptation of the processes and structures of the enterprise in an ERP environment.Design/methodology/approachThis paper presents a fundamental methodology based on goal directed project management (GDPM) principles which supports the complicated process of implementation and optimal adaptation (IOA) of an ERP system.FindingsBy implementing this methodology it was found that it is able to control and reduce the time and the cost of implementation and to achieve optimal adaptation of the processes and structures of the enterprise in an ERP environment.Research limitations/implicationsBased on the above methodology a system must be developed, which will aim at providing the project manager with the ability to create all the necessary elements for the management and realization of the project and to lead the consultant during the IOA process of ERP systems.Practical implicationsThis methodology was connected to, and tested with the operations and capabilities of an ERP commercial package in one of the leading software houses in Greece. The functional result of this methodology was proved to support considerably the process of IOA of SEn in the companies‐customers.Originality/valueThis paper provides a generic research in this technological field concerning small or medium‐sized enterprises based on the GDPM principles which aims at the facilitation and effective guidance for the installation process IOA in all stages and in all levels of analysis.

Over the past several years, there have been intensive discussions about the importance of knowledge management (KM) in our society. Nowadays, it is commonly accepted that many KM disciplines and practices are relevant to the social‐level knowledge‐based development. In this context, the new theme of “knowledge cities” came to the front. This paper attempts on the one hand to define the concept in a coherent way – presenting also its main implications and benefits – and on the other hand, to examine – on a worldwide scale – the different models of knowledge cities as well as modes of practice. The authors were based on a broad range of published works, including papers, books, reports and Web sites. The main approach was to briefly present the existing views of the concept, accompanied by some criteria determining a knowledge city. The authors also tried to provide a meaningful and concise review of existing cases, avoiding to get into many confusing details. This review provided valuable input for the definition of the key success factors and main benefits related to knowledge cities. This new concept is currently a main topic of interest for the research community and practitioners. It becomes clear that it has important benefits and in this way, focused research is needed towards many directions, in order for it to become a part of our life in near future. This integrated review is a very useful source of information for academics and practitioners who want to be acquainted with the knowledge cities concept.

Environmental legislation and its enforcement has undoubtedly forced the textile industry to be rather cautious in selecting the appropriate processes and equipment. The most efficient, economic and minimal environmental pollution processing methods will be increasingly demanded throughout the 1990s. However, the majority of the textile industry consists of small and medium enterprises, where the lack of expertise on the use of best available techniques leads to levels of operation far away from the optimal. An expert system for a priori economic evaluation of potential interventions in the textile manufacturing processes and equipment is necessary to support decision making in the management level. This paper presents such an expert system, designed and implemented in four stages: formal description of the key factors that affect the dyeing process in the textile industry, development of models for the representation of relevant information, development of models for the representation of knowledge and integration of the above‐mentioned models in a unified information system that supports the decision‐making process in the management of textile enterprises.

Managing large amounts of information and efficiently using this information in improved decision making has become increasingly challenging as businesses collect terabytes of data. Intelligent solutions, based on neural networks (NNs) and genetic algorithms (GAs), to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. The current study provides an overview for the operations researcher of the neural networks and genetic algorithms methodology, as well as their historical and current use in business. The main aim is to present and focus on the wide range of business areas of NN and GA applications, avoiding an in‐depth analysis of all the applications – with varying success – recorded in the literature. This review reveals that, although still regarded as a novel methodology, NN and GA are shown to have matured to the point of offering real practical benefits in many of their applications.

Some analysts have claimed that the volatility of an asset is caused solely by the random arrival of new information about the future returns from the asset. Others have claimed that volatility is mainly caused by trading. In any case it is a common belief that volatility is of great importance in finance and it is the factor that plays the most important role in determining option prices. This paper discusses the development of a decision support system (D‐TIFIS) for options trading based on volatility forecasting. In order to evaluate the system, data were used from the Greek FTSE/ASE 20 stock index as well as at the money call and put prices on the specific index.

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.

A great challenge for today’s companies is not only how to adapt to the changing business environment but also how to gain a competitive advantage from the way in which they choose to do so. As a basis for achieving such advantages, companies have started to seek to improve the performance of various operations. Forecasting is one of them; it is important to firms because it can help ensure that effective use of resources is made. In the market there are a number of off‐the‐shelf system products, which provide forecasts. The new trend, of moving traditional software packages to Web services, has pushed forecasting to a new dimension, named by the authors as “e‐forecasting”. In this paper, a first approach to e‐forecasting is made by throwing light on several aspects and a survey is presented which aims at identifying existing Web forecasting services.

Intelligent solutions, based on expert systems (ES), to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. Expert systems are being developed and deployed worldwide in myriad applications, mainly because of their symbolic reasoning and its explanation capabilities. Provides an overview for the operations researcher of the expert systems methodology, as well as their historical and current use in business. Aims to present and focus on the wide range of business areas of ES applications, avoiding an in‐depth analysis of all the applications ‐‐ with varying success ‐‐ recorded in the literature. Reveals that, although still regarded as a novel methodology, ES are shown to have matured to the point of offering real practical benefits in many of their applications.

Companies deal with many decision‐making processes whose impact on the global performance can be very strong. As a consequence, the role of the decision support systems (DSSs) within the organization is critical. Considering the imprecise or fuzzy nature of the data in real‐world problems, it becomes obvious that the ability to manage uncertainty turns out to be a crucial issue for a DSS. In this framework, this paper discusses the key role of fuzzy logic (FL) in the DSSs, presents new applications of FL in DSSs in various sectors and identifies new challenges and new directions for further research.

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.

During the last decade, many companies have made large investments in the development and implementation of enterprise resource planning (ERP) systems. However, only few of these systems developed or installed have actually considered maintenance strategies. Maintenance is a complex process that is triggered by planned periodic repair (scheduled or planned maintenance), equipment breakdown or deterioration indicated by a monitored parameter (unplanned or emergency maintenance). This process requires planning, scheduling, monitoring, quality assurance and deployment of necessary resources (workshop, manpower, machines, equipment, tools, spare parts, materials). Proper design and integration of maintenance management into ERP systems enable enterprises to effectively manage their production planning and scheduling, as well as to analyze their maintenance history so as to carry out cost analysis and produce future projections of failure trends. The present work presents the design of an object‐oriented maintenance management model and its integration into an ERP system. The proposed model was designed towards the development of innovative industrial software regarding the optimum management of maintenance in a wide range of business areas.

Knowledge management has recently received considerable attention in the computer information systems community and is continuously gaining interest from industry, enterprises and government. As we move towards building knowledge organizations, knowledge management in combination with information management will play a fundamental role towards the success of transforming individual knowledge into organizational knowledge. In this framework, this paper discusses the key concepts of human‐computer interaction in knowledge management, identifies new challenges of knowledge management for Web‐based business and proposes a “user agent architecture” for knowledge management in e‐learning environments. User agents use artificial neural network technology and can be used in various e‐learning or e‐training environments, in order to provide them with means of managing information stored, filtering content and enabling better knowledge adoption on behalf of their users.

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.

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.

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.

From the very earliest moments in the modern history of the computer, scientists have dreamed of creating advanced systems which would simulate human meditation and reasoning. Of all the modern technological quests, this research to create artificially intelligent computer systems has been one of the most ambitious and fascinating. Although attempts had been made more than 30 years ago to develop and apply such systems to the medical sciences, the field languished for decades. In this framework, this paper aims to share thoughts and estimations on the important role of expert systems in medicine and address their future as well as the trends that are foreseen in this area.

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.

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.