Purpose – The integration of management systems is a common need nowadays, thus several paradigms exist in the bibliography for relevant efforts. However, the basic effort seems to be mainly at the direction of aligning processes and documents, taking into account only one of four typical views of organisations' modelling (the function view). Since the function view has been widely studied, this paper aims to focus on the organisation/decision view. Design/methodology/approach – The proposed approach focuses on the integrated management system (IMS) with respect to the organisation/decision view and offers a control mechanism which guarantees that requirements from all standards will be taken into consideration, while it proposes the use of a well-known multi-criteria decision making technique to support the decision makers. The paper focuses on the organisation/decision view, illustrated through a real case from the chemical industry. Findings – It is concluded that the integration of management sub-systems into one IMS should be done with respect to each one of the four enterprise modelling views, namely function, information, resource and organisation/decision view. Research limitations/implications – The proposed approach is general and can be applied to many integrated systems where decisions have to be taken. However, the selection of the analytic network process as a decision support tool implies that the decision involves both qualitative and quantitative criteria. In cases where only qualitative or only quantitative criteria exist, another decision support tool may be superior. Originality/value – The originality of the paper stems from the consideration of the organisation/decision view rather than the function view that mostly appears in literature.

The continuous increase in global maritime freight transport has led to an increase in emissions. The port of Heraklion was selected as a case study to investigate the environmental impact of shipping in wider areas. Two different maritime fuels were examined: the conventional maritime fuel, marine diesel oil (MDO), and an alternative maritime fuel, liquified natural gas (LNG). To carry out this study, real data from the port of Heraklion, the Lloyd’s Register Fairplay (LRF) Sea-Web database, and literature reviews were used. The bottom-up method was adopted for data processing. The results of this study demonstrate that alternative maritime fuels, such as LNG, could drastically reduce SO₂, NOx, PM, and CO₂ emissions.

The importance of stakeholders’ analysis for the effective management of risks in any business sector has been widely recognized and depicted in International Organization for Standardization (ISO) standards. This kind of analysis is even more necessary in businesses and organizations dealing with significant technological and market changes, such as the provision and usage of Liquefied Natural Gas (LNG) as a marine fuel. In the LNG bunkering industry, several methods have been proposed to support risk management. However, they all suffer from an important drawback: they guide risk management mainly to the identification, analysis, and control of potential accidental events within a health and safety or a technical reliability analysis framework, failing to structure the correlation of risks with the actual actors, i.e., the numerous stakeholders whose decisions may influence directly or indirectly the organization’s objectives. This paper presents a method to systematically analyze the role of stakeholders and their ability to pose threats and/or opportunities to an organization. The proposed approach employs the Social Network Analysis (SNA) methodology to model and analyze stakeholder interests, interactions, and relationships that are important to the organization’s objectives. The method is applied in a small-scale LNG bunkering project at a Greek port.

In the new era of knowledge economy, knowledge and the processes to generate and manage it are considered as 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 society, except from the business world. Today, there is a consensus among researcher's and practitioner's communities that the challenges facing modern societies, call for development strategies that are knowledge-based. In this context, the theme of Knowledge Cities (KCs) came to the front. The review of literature reveals that the process of designing Knowledge-Based Development (KBD) strategies for KCs is complex and not appropriately supported by decision support methodologies and/or intelligent systems. In this paper, the authors, based on a previously presented methodology for the formulation of a KBD strategy for KCs, propose an AI-based decision support system for designing such strategies, by selecting and prioritising the most appropriate interventions and actions. The system consists of two sub-systems: the first (developed using the technology of Expert Systems) assess the necessity of a particular intervention and proposes its most appropriate form. The second prioritises the selected interventions based on Multi-Criteria Decision Making. The authors also present the successful preliminary results of the system?s pilot application to a Greek municipality.