Understanding inter-organizational decision coordination

This article develops a theoretical framework to investigate the interaction and coordination of decision-making processes in a supply chain with multiple and inter-dependent suppliers and customers. Design/Methodology/Approach: Three longitudinal case studies on the decision coordination processes between a European toy supplier and three retailers. Findings: The case studies found different mental models, decision-making behaviours, coordination behaviours and ordering behaviours even though the toy supplier and the three retailers observed quite the same material flow behaviours. The study found explanations for these diverse behaviours by analyzing the mental models and decision-making behaviours of each involved party. Originality/value: The findings explain the conditions which lead to undesirable mental models and decision-making behaviours which affect the coordination of decisions among supply chain members

"It's all up here": adaptation and improvisation within the modern project

This paper considers organisational improvisation, and in particular, adaptation as a specific component of improvisational work(Miner et al., 2001), and how it may assist in resolving or assisting with some of the challenges surrounding recent shifts in our understanding of project-based management. Examples focus on the use of adaptation to cope with ambiguity and uncertainty, caused by execution in problematic and turbulent organisational environments. The literature on improvisation suggests that adapting previously successful interventions reduces and manages the risk of improvising by engaging with the 'adaptation component of organisational improvisation. This practice assists in ensuring that the additional risk of completely novel activity is avoided. This paper explores adaptation within the project domain, and also unpicks the rhetoric from the reality of adaptation within projects, confirming its benefits, setting out the circumstances where experience informs the practice, and offering readily usable and applicable insights

A video life-world approach to consultation practice: The relevance of a socio-phenomenological approach

This article discusses the [development and] use of a video life-world schema to explore alternative orientations to the shared health consultation. It is anticipated that this schema can be used by practitioners and consumers alike to understand the dynamics of videoed health consultations, the role of the participants within it and the potential to consciously alter the outcome by altering behaviour during the process of interaction. The study examines health consultation participation and develops an interpretative method of analysis that includes image elicitation (via videos), phenomenology (to identify the components of the analytic framework), narrative (to depict the stories of interactions) and a reflexive mode (to develop shared meaning through a conceptual framework for analysis). The analytic framework is derived from a life-world conception of human mutual shared interaction which is presented here as a novel approach to understanding patient-centred care. The video materials used in this study were derived from consultations in a Walk-in Centre (WiC) in East London. The conceptual framework produced through the process of video analysis is comprised of different combinations of movement, knowledge and emotional conversations that are used to classify objective or engaged WiC health care interactions. The videoed interactions organise along an active or passive, facilitative or directive typical situation continuum illustrating different kinds of textual approaches to practice that are in tension or harmony. The schema demonstrates how practitioners and consumers interact to produce these outcomes and indicates the potential for both consumers and practitioners to be educated to develop practice dynamics that support patient-centred care and impact on health outcomes

Reusable Knowledge-based Components for Building Software Applications: A Knowledge Modelling Approach

In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach

Common vocabularies for collective intelligence - work in progress

Web based applications and tools offer a great potential to increase the efficiency of information flow and communication among different agents during emergencies. Among the different factors, technical and non technical, that hinder the integration of an information model in emergency management sector, is a lack of a common, shared vocabulary. This paper furthers previous work in the area of ontology development, and presents a summary and overview of the goal, process and methodology to construct a shared set of metadata that can be used to map existing vocabulary. This paper is a work in progress report

Notions of Knowledge Management

{Excerpt} Knowledge management is getting the right knowledge to the right people at the right time, and helping them (with incentives) to apply it in ways that strive to improve organizational performance. Data are facts, and information is interpreted data. Knowledge is created and organized by flows of information, shaped by their holder. It is tacit or explicit. Tacit knowledge is nonverbalized, intuitive, and unarticulated knowledge that people carry in their heads. It is hard to formalize and communicate because it is rooted in skills, experiences, insight, intuition, and judgment, but it can be shared in discussion, storytelling, and personal interactions. It has a technical dimension, which encompasses skills and capabilities referred to as know-how. It has a cognitive dimension, which consists of beliefs, ideals,values, schemata, or mental models. Explicit knowledge is codified knowledge that can be expressed in writing, drawings, or computer programs, for example, and transmitted in various forms. Tacit knowledge and explicit knowledge are mutually complementary forms of meaning

Building Machines That Learn and Think Like People

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar