ABSTRACT

Higher education institutions (HEIs) in the UK are increasingly engaging in work-based learning. The tripartite relationship between the HEI, the employer and the employee is viewed to be of great significance in work-based learning, not only in the initial stages of procurement of a contract, but also in designing and delivering the programme to meet the employer and employee needs, and those of the HEI, to make the programmes successful. This paper is based on one theme related to a larger EU-funded project on work-based learning leading to qualifications. Based on in-depth interviews at a post-1992 university in the UK with a range of staff including executive, senior management, managerial, teaching and administrative staff, we focus on this theme, to analyse employer engagement from the perspective of the HEI. We recommend strategies to enhance the tripartite relationship for the benefit of those involved and to improve policy and practice in the field. These include a strategic approach to work-based learning and regarding it as an integral part of higher education activity rather than a supplementary pursuit.

Highlights• Develop an aggregated research schema for VE, ASC, and SC collaboration • Propose a conceptual model for the relationship between VE and ASC • Explore drivers and enablers of agility • Provide rich empirical evidence on impact of VE on ASC • Present theoretical insights and practical implications for managers ACCEPTED MANUSCRIPT ABSTRACTIn the recent advanced information communications and technology (ICT) era, collaborating virtually and temporarily in supply chains (SCs) to receive mutual benefits such as agility while sharing resources and information becomes an important strategy for enterprises that seek to increase their competitiveness and to optimise their processes and resource usage. As a dynamic and temporary form of alliance from the resource perspective, virtual enterprises (VEs) may contribute network resource heterogeneity and sustain competitive advantage. In addition, agility is suggested as a rare, valuable, network resource that is difficult to imitate and that cannot easily be substituted by other attributes.Although many researchers have investigated VEs and their agility, the research pays less attention to the relationship between VEs and agility in complex SC situations. This paper therefore investigates the relationship between VE and agility in SCs (ASCs) and explores drivers and enablers of agility and outcomes. To clarify the relationships between factors a structural equation model (SEM) is adopted to examine the model fit according to the measurement variables and supporting hypotheses. The results provide rich empirical evidence of the beneficial impact of VEs on ASCs, and theoretical and managerial insights that can be used to strengthen the drivers, enablers and capabilities to enhance the effectiveness of VE collaboration in ASCs in a global and dynamic context. Also, the analysis results can aid a decision maker which ones of the factors are the important ones that he or she should devote more resources and efforts on.

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The UK National Health Service (NHS) is faced with problems of managing patient discharge and preventing the problems that result from it such as frequent readmissions, delayed discharge, long waiting lists, bed blocking and other such consequences. The problem is exacerbated by the growth in size, complexity and the number of chronic diseases in the NHS. In addition, there is an increase in demand for high quality care, processes and planning. Effective Discharge Planning (DP) requires practitioners to have appropriate, patient personalised and updated knowledge in order to be able to make informed and holistic decisions about a patients’ discharge. This paper examines the role of Knowledge Management (KM) in both sharing knowledge and using tacit knowledge to create appropriate patient discharge pathways. The paper details the factors resulting in inadequate DP, and demonstrates the use of Internet of Things (IoT) and Machine2Machine (M2M) as candidate technologies and possible solutions which can help reduce the problem. The use of devices that a patient can take home and devices which are perused in the hospital generate information, which can serve useful when presented to the right person at the right time, thus harvesting knowledge. The knowledge when fed back can support practitioners in making holistic decisions with regards to a patients’ discharge.