Towards a human resources management approach in supply chain management

Supply chain management (SCM) has grown as a discipline since the field attracted attention in the 1980s. However, it is observed that effective implementation of SCM is limited because the current focus is too task-based and information-centric. The concept is often conflated, in practice, with subcontractor management, where numerical flexibility is pertinent. At the same time, consideration of human resources management (HRM) in SCM has been limited. Strategic fit within supply chains tends to emphasise taskbased numerical flexibility, rather than genuine consideration and development of human resources. On the other hand, HRM has, until recently, rarely taken into account interorganisational characteristics that typify the construction industry. Therefore, this research intends to plug the gap by examining the use of human resources in construction supply chains, with a view of developing good practice for HRM in construction SCM. To achieve this, a two-phase research methodology comprising a scoping phase and case study phase will be ensued

On the efectiveness of several market integration measures: an empirical analysis

Many market integration measures are operationalized to compute their numerical values during a period characterized by the lack of stability ad market turmoil. The results of the tests give their degree of effectiveness, and reveal that the measures based on the principles of asset valuation, versus statistical measures, more clearly yield the level of integration of financial markets. Besides, cross market arbitrage-linked measures and equilibrium models-linked measures provide complementary information and reflect different properties, and consequently, both types of measures may be useful in practice

Convergence and regularization for monotonicity-based shape reconstruction in electrical impedance tomography

The inverse problem of electrical impedance tomography is severely ill-posed, meaning that, only limited information about the conductivity can in practice be recovered from boundary measurements of electric current and voltage. Recently it was shown that a simple monotonicity property of the related Neumann-to-Dirichlet map can be used to characterize shapes of inhomogeneities in a known background conductivity. In this paper we formulate a monotonicity-based shape reconstruction scheme that applies to approximative measurement models, and regularizes against noise and modelling error. We demonstrate that for admissible choices of regularization parameters the inhomogeneities are detected, and under reasonable assumptions, asymptotically exactly characterized. Moreover, we rigorously associate this result with the complete electrode model, and describe how a computationally cheap monotonicity-based reconstruction algorithm can be implemented. Numerical reconstructions from both simulated and real-life measurement data are presented

Geometric Interpretation of Theoretical Bounds for RSS-based Source Localization with Uncertain Anchor Positions

The Received Signal Strength based source localization can encounter severe problems originating from uncertain information about the anchor positions in practice. The anchor positions, although commonly assumed to be precisely known prior to the source localization, are usually obtained using previous estimation algorithm such as GPS. This previous estimation procedure produces anchor positions with limited accuracy that result in degradations of the source localization algorithm and topology uncertainty. We have recently addressed the problem with a joint estimation framework that jointly estimates the unknown source and uncertain anchors positions and derived the theoretical limits of the framework. This paper extends the authors previous work on the theoretical performance bounds of the joint localization framework with appropriate geometric interpretation of the overall problem exploiting the properties of semi-definiteness and symmetry of the Fisher Information Matrix and the Cram{\`e}r-Rao Lower Bound and using Information and Error Ellipses, respectively. The numerical results aim to illustrate and discuss the usefulness of the geometric interpretation. They provide in-depth insight into the geometrical properties of the joint localization problem underlining the various possibilities for practical design of efficient localization algorithms.Comment: 30 pages, 15 figure