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The heterogeneity that characterises international research and development (R&D) teams often brings with it a wide spectrum of knowledge resources potentially relevant for the operation of the team. The study looks at a context where a positive relationship exists, and high levels of knowledge sharing take place between team members, referred to as knowledge orchestration, as a prerequisite for successful outputs in international research. The research involved 93 members of R&D teams working –either directly or indirectly, on the domain of industrial mortars. Within that domain, research participants are focused on the search for innovative solutions to improving the energy efficiency of buildings and the production of renewable energy. Partial Least Squares (PLS) using the SmartPLS allowed for the analysis of the data collected from practitioners. The results show that knowledge orchestration has a significant mediation effect between the heterogeneity of knowledge created by international R&D and their outputs.

The integration of advanced technologies within education has frequently enhanced teaching. In higher education it is not a surprise that using the latest developments in cloud computing improves learning practices and thus ensures they are more interactive, available, and convenient. The ease of integration, collaboration, and sharing of information and knowledge made possibleby cloud computing will be further enhanced if this technical advancement is used wisely and in a foolproof manner. In this paper, a SWOT analysis of the impact of cloud computing on higher education methodologies is presented. A SWOT analysis is here demonstrated to be a helpful guide in decision-making for all higher education institutions when considering the migration of their present learning systems to cloud based systems.

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.

This panel will discuss key aspects of knowledge management (KM) education in response to challenges posed by the necessity to improve KM as a discipline and an established professional field. Through panelists’ thought-provoking presentations and interactions with the audience, the discussion will address KM education from the starting why, what, who, where and when perspectives to the end result and understanding of how to approach KM education in the future.

One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework with customizable wireless interfaces and plug‘n’play capability to easily interconnect third party sensor devices. It caters to wireless body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual development and remote deployment model. The complementary visual InferenceEngineEditor that comes with the package enables artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications.

As more and more organisations move from on-premise to on-demand software solutions in order to minimise overhead costs, the Enterprise Resource Planning (ERP) providers begin to offer their well-established best business processes as cloud based IT solutions. As a result, ERP software previously reserved for large organisations mainly due to heavy costs associated with the initial purchase of the software, its licensing costs and subsequent configuration and maintenance, begins to open up to Small and Medium Enterprises (SMEs). With more and more Software as a Service (SaaS) ERP solutions on the market, SMEs are beginning to consider and implement these solutions as opposed to in-house developed applications, in a bid to offer better customer relationship, gain new markets and increase profits, amongst other benefits. As this study reveals, while deployment model is a key advantage in enabling organisations to minimise costs, certain critical factors as well as some barriers need to be addressed to enable organisations to successfully implement these systems. This paper aims to identify and evaluate common problems experienced in the implementation as well as post-implementation stage of Software as Service ERP systems by Small and Medium Enterprises. Qualitative data was collected from five European and US companies, which implemented SaaS ERP, by means of a set of semi-formal interviews and online questionnaire.

The term “knowledge warehousing” has been used by different research communities since the late 1990s. Use of such a concept in the literature varies from an unnecessary upgrade of a data warehouse to an up-market label for systems traditionally used to store and disseminate data and information. This paper provides a critical review of major works within the knowledge warehousing domain. Its aim is to raise awareness within the knowledge management research and practice communities about reasons why knowledge warehousing has not become part of accepted terminology a decade after first references to the term appeared in the literature.

Ever since the late 1990s, different research communities have used the term 'knowledge warehousing' to refer to several types of IT-based tools. An extensive review of the literature on this topic revealed that existing approaches to knowledge warehousing may be classified into three completely different categories. None of the studies reviewed has been able to provide a compelling justification for their suitability. Given such lack of clarity, it seems that we are just experiencing a 'syntactic upgrade' of the concept of data warehousing into a new, more fashionable term. Furthermore, it remains unclear whether the human nature of knowledge would even allow such a resource to be warehoused. On the basis of advantages and limitations of existing notions of knowledge warehousing, this paper aims to provide tools required to unify existing disparate views of knowledge warehousing by focusing on aims of approaches rather than terminology.