A Knowledge Management Process-Based Approach to Support Corporate Crisis Management

In the crisis-prone and complex contemporary business environment, modern organisations and their supply chains, large and small, are challenged by crises more than ever. Knowledge management has been acknowledged as an important discipline able to support the management of complexity in times of crisis. However, the role of effective knowledge retrieval and sharing in the process of crisis prevention, management and survival has been relatively underexplored. In this paper, it is argued that organisational crises create additional challenges for knowledge management, mainly because complex, polymorphic and both structured and unstructured knowledge must be efficiently harnessed, processed and disseminated to the appropriate internal and external supply chain actors, under specific time constraints. In this perspective, a process-based approach is proposed to address the knowledge management needs of organisations during a crisis and to help management in establishing the necessary risk avoidance and recovery mechanisms. Finally, the proposed methodological approach is applied in a knowledge- intensive Greek small and medium enterprise from the pharmaceutical industry, producing empirical results, insights on knowledge pathologies during crises and relevant evaluations.

AR-based Technoself Enhanced Learning Approach to Improving Student Engagement

The emerging technologies have expanded a new dimension of self – ‘technoself’ driven by socio-technical innovations and taken an important step forward in pervasive learning. Technology Enhanced Learning (TEL) research has increasingly focused on emergent technologies such as Augmented Reality (AR) for augmented learning, mobile learning, and game-based learning in order to improve self-motivation and self-engagement of the learners in enriched multimodal learning environments. These researches take advantage of technological innovations in hardware and software across different platforms and devices including tablets, phoneblets and even game consoles and their increasing popularity for pervasive learning with the significant development of personalization processes which place the student at the center of the learning process. In particular, augmented reality (AR) research has matured to a level to facilitate augmented learning, which is defined as an on-demand learning technique where the learning environment adapts to the needs and inputs from learners. In this paper we firstly study the role of Technology Acceptance Model (TAM) which is one of the most influential theories applied in TEL on how learners come to accept and use a new technology. Then we present the design methodology of the technoself approach for pervasive learning and introduce technoself enhanced learning as a novel pedagogical model to improve student engagement by shaping personal learning focus and setting. Furthermore we describe the design and development of an AR-based interactive digital interpretation system for augmented learning and discuss key features. By incorporating mobiles, game simulation, voice recognition, and multimodal interaction through Augmented Reality, the learning contents can be geared toward learner's needs and learners can stimulate discovery and gain greater understanding. The system demonstrates that Augmented Reality can provide rich contextual learning environment and contents tailored for individuals. Augment learning via AR can bridge this gap between the theoretical learning and practical learning, and focus on how the real and virtual can be combined together to fulfill different learning objectives, requirements, and even environments. Finally, we validate and evaluate the AR-based technoself enhanced learning approach to enhancing the student motivation and engagement in the learning process through experimental learning practices. It shows that Augmented Reality is well aligned with constructive learning strategies, as learners can control their own learning and manipulate objects that are not real in augmented environment to derive and acquire understanding and knowledge in a broad diversity of learning practices including constructive activities and analytical activities.