Increasing productivity of knowledge workers by ontological training

Proceedings of the International Conference «Business Sustainability BS 2008», Minho, Portugal, 2008. pp. 158-163knowledge-driven organizations, productivity of knowledge workers, learning, thinking, analyst training,

Contested modelling

We suggest that the role and function of expert computational modelling in real-world decision-making needs scrutiny and practices need to change. We discuss some empirical and theory-based improvements to the coupling of the modelling process and the real world, including social and behavioural processes, which we have expressed as a set of questions that we believe need to be answered by all projects engaged in such modelling.  These are based on a systems analysis of four research initiatives, covering different scales and timeframes, and addressing the complexity of intervention in a sustainability context. Our proposed improvements require new approaches for analysing the relationship between a project’s models and its publics.  They reflect what we believe is a necessary and beneficial dialogue between the realms of expert scientific modelling and systems thinking.  This paper is an attempt to start that process, itself reflecting a robust dialogue between two practitioners sat within differing traditions, puzzling how to integrate perspectives and achieve wider participation in researching this problem space.&nbsp

An Ontology for Product-Service Systems

Industries are transforming their business strategy from a product-centric to a more service-centric nature by bundling products and services into integrated solutions to enhance the relationship between their customers. Since Product- Service Systems design research is currently at a rudimentary stage, the development of a robust ontology for this area would be helpful. The advantages of a standardized ontology are that it could help researchers and practitioners to communicate their views without ambiguity and thus encourage the conception and implementation of useful methods and tools. In this paper, an initial structure of a PSS ontology from the design perspective is proposed and evaluated

An Ontology-Based Knowledge Modelling for Sustainable Entrepreneurship Domain

Sustainable entrepreneurship (SE) focuses on entrepreneurial activities taking into account environmental and social issues, not only by paying attention to economic issues. While the concept of SE is a prominent stream for modern entrepreneurship, the following questions arise: how enterprises can run a business and implement Sustainable Development Goals (SDG) and which factors can support or constrain SE? Research on SE suggests that that identifying and implementing sustainable development opportunity is more complex for the entrepreneur than the recognition of non-sustainable opportunity. Therefore this article contributes to the advancement of sustainable entrepreneurship research by offering an ontology-based approach collecting factors from the current literature review and incorporating different lines of research that can influence further sustainable entrepreneurial strategies. The applied research methodology exploits a previously elaborated bibliometric analysis which included a systematic literature review conducted using the PRISMA methodology. The condensed immense amount of bibliometric information and further co-occurrence analysis of keywords determining SE factors is a basis for constructing ontology-based model. This model offers a classification schema of sustainable entrepreneurship factors as well as a tool performing knowledge from being machine-readable to machine-understandable

An ontology for strongly sustainable business models: Defining an enterprise framework compatible with natural and social science

Business is increasingly employing sustainability practices, aiming to improve environmental and social responsibility while maintaining and improving profitability. For many organizations, profit-oriented business models are a major constraint impeding progress in sustainability. A formally defined ontology, a model definition, for profit-oriented business models has been employed globally for several years. However, no equivalent ontology is available in research or practice that enables the description of strongly sustainable business models, as validated by ecological economics and derived from natural, social, and system sciences. We present a framework of strongly sustainable business model propositions and principles as findings from a transdisciplinary review of the literature. A comparative analysis was performed between the framework and the Osterwalder profit-oriented ontology for business models. We introduce an ontology that enables the description of successful strongly sustainable business models that resolves weaknesses and includes functionally necessary relationships

Knowledge Management for Public Administrations: Technical Realizations of an Enterprise Attention Management System

The improvement of governments’ efficiency has gained great importance and validity especially in the current times of economic downturn. E-Government constitutes the most contemporary techno-managerial proposition in the track of possible interventions. The paper addresses, more specifically, empowerments necessitated by Public Administration (PA) organizations. Anchored on the needs of three real-life cases, the paper describes the conception and the realization of an IT artefact together with its methodological appeals aiming at improving information access and delivery and thus PAs’ decision making capacity. Our proposition constitutes a novel approach for managing users’ attention in knowledge intensive organizations which goes beyond informing a user about changes in relevant information towards proactively supporting the user to react on changes. The approach is based on an expressive attention model, which is realized by combining ECA (Event-Condition-Action) rules with ontologies. The technical realizations described in the paper constitute the underlying infrastructure of an Enterprise Attention Management System