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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.

In 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.

The 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.

The 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.

Recommended directions for further action research are presented.

The 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.

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 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.

Based 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.

The 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.

It would be interesting and useful to deepen the analysis made by the authors and look for more fundamental reasons behind their observations.

The main advantage of this paper is that it proposes a simplified conceptual model for stakeholder knowledge partnerships in knowledge cities.

During 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.

The 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.

Based 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.

The 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.

The 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.

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.

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.

The purpose of this paper is to introduce the JKM 2010 annual special issue on knowledge based development (KBD) with reference to the multi‐level analysis characteristic of the field.

A description of the knowledge management approach at ESOC (European Space Operations Centre of the European Space Agency) is provided first. At the core of this approach is the breakdown of knowledge in individual technical domains followed by coverage analysis and criticality assessment. Such a framework becomes the reference for best knowledge acquisition, transfer and storage locus identification and subsequent knowledge management practices and guidelines.

KBD provides an integrated framework to account for multidisciplinary analyses and multilevel practices in knowledge capital generation, distribution and utilization.

The collection of papers included in the annual special issue on KBD provides a representative, composite view of the research topics and applications concerns in the field. Involving a number of disciplines and levels of analysis, issues ranging from the technological gatekeeper to global knowledge flows show the interdependence of KBD concepts and tools.

To 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.

A 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.

The 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.

The 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.

The model can be used in any area of information and knowledge management.

Using the model, SMEs can achieve the integration of ERP and KM, which is proven to be a necessity for them in the knowledge economy.