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Purpose – The purpose of this paper is to provide a system for the performance evaluation of humanitarian supply chains. The system will help humanitarian organizations (HOs) to make better decisions, improve their performance, and provide accountability, as well as helping them measure their operational performance during disaster response and reconstruction projects. Design/methodology/approach – A holistic and implementable performance measurement system was developed to measure the operational performance of HOs during disaster response and reconstruction projects. The system is divided into five categories with several key performance indicators (KPIs) being identified for each; identifiers are qualitative and quantitative, as well as financial and non-financial. Findings – Empirical testing of the system demonstrated the low use of existing performance indicators in humanitarian supply chains and the possible added value for HOs to improve their operational efficiency. Social implications – The performance measurement system could help HOs improve their operations and resource allocation. Originality/value – The paper is one of the first research contributions in which a sample of developed KPIs is empirically tested in various HOs. Prior to this paper, a limited number of articles examined the performance of HOs, and no defined system of KPIs existed. By analyzing real results in the field of the humanitarian projects and applying the proposed performance measurement system, it will be possible to define a set of best approaches to improve the effectiveness and efficiency of humanitarian supply chains.

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In recent years the increase in time-based competition and the growth of e-commerce have put pressure on managers to reduce the costs of warehouse design and management activities. This paper presents a new integrated approach to support the decision making process in optimising a picker to part, forward-reserve, less than unit load order picking system. An analytical model and a multi-parametric dynamic model to quickly estimate the travelled distance during a picking cycle are introduced. The factorial analysis of several what-if scenarios reveals which factors and combinations of factors are the most critical in affecting the picking system's response

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