Development Policies and Sectors

This paper is part of a greater effort of the London Severe Injury Working Group that is aiming to the improvement of care, treatment and transfer of severely injured patients. The problem we address in this paper emanates from the Location Set Covering Problem literature. We sought to position the minimum number of trauma centers within a network of existing hospitals and minimize the total traveling time of patients, from the place of injury to the hospital of final treatment in such a way that everyone in the entire population of London can reach a trauma center within acceptable time limits. A mathematical programming approach has been adopted in order to solve the problem. The created model proved very useful in enlightening the problem and providing a set of solutions easily understandable by all parts involved in the final decision. The proposed configuration of the trauma centers was provided to the London Severe Injury Working Group for subsequent decisions.

Increased competition and uncertainty characterise the new economy, introducing significant pressures to supply chain participants, calling for capital investments only in value adding/revenuegenerating assets. The tendency of companies to expand their control through the entire supply chain seems to attract significant managerial attention. On the other hand, large manufacturer and distributor firms have developed specific competences that do not expand to all the levels of the supply chain. In order to confront the lack of knowledge and expertise companies can either outsource the specific operation or acquire a company that is specialized in the specific field. In this paper we focus on warehousing decisions and investigate three different warehousing policies and ownership structures of the warehousing facilities.

In this paper we address the problem of inventory positioning, i.e., the determination of the supply chain node where inventory should be held, to minimize holding costs given a pre-specified order fill rate. A single-echelon inventory system with multiple products models the problem. The value of inventory is assumed to be an increasing function of the amount of processing performed at upstream nodes, while achieved fill-rates are dependent on the distance or time between the inventory storage and customer locations. We propose a novel analytical approach to solve the problem for the case of normally distributed demand that is based on iterative calculations of inventory holding costs at the various potential inventory locations.

A decision support model (DSM) is presented and implemented in order to identify probable and realistic export opportunities for Greece. The aim of the model is to select those combinations of products and countries of destination (markets) that are attractive based on widely recognized criteria (such as country risk indicators, macroeconomic data, market shares, accessibility of destination country, degree of market concentration, etc.). The DSM consists of a filtering process during which the less attractive export opportunities are successively eliminated in order to focus on those markets that have the desired characteristics. International trade data at the HS six-digit level up to 2011 where used. The results indicate that there exist significant export opportunities for Greece. Export opportunities are listed and categorized according to criteria such as the market characteristics of the destination country and Greece’s market share.

This paper is part of a greater effort of the London Severe Injury Working Group that is aiming to the improvement of care, treatment and transfer of severely injured patients. The problem we address in this paper emanates from the Location Set Covering Problem literature. We sought to position the minimum number of trauma centers within a network of existing hospitals and minimize the total traveling time of patients, from the place of injury to the hospital of final treatment in such a way that everyone in the entire population of London can reach a trauma center within acceptable time limits. A mathematical programming approach has been adopted in order to solve the problem. The created model proved very useful in enlightening the problem and providing a set of solutions easily understandable by all parts involved in the final decision. The proposed configuration of the trauma centers was provided to the London Severe Injury Working Group for subsequent decisions.

A problem that arises across modern supply chains due to the intense pressures of the new economy is that of postponing, i.e., pushing inventories to low value locations. On the other hand, customers require short delivery times and immediate response to orders, thus calling for inventory availability near their locations. In this paper we addresses inventory positioning, i.e., the determination of the supply chain node where inventory should be held to minimize holding costs given a pre-specified order fill rate. A single-echelon inventory system with multiple products models the problem. Inventory value is assumed an increasing function of the amount of processing performed at upstream nodes, while achieved fill-rates are dependent on the distance-time between the inventory and customer locations. We propose a novel analytical approach to solve the problem for the case of normally distributed demand that is based on iterative calculations of inventory holding costs at the various potential inventory locations. An example illustrates the mechanics of the approach in practical situations.

The export performance of the manufacturing sector in
the EU19 is examined. In addition, the competitiveness of
the manufacturing sector is analyzed based on the index
of Revealed Symmetric Comparative Advantage (RSCA).
Manufactured products are divided into four categories
based on the technology intensity they incorporate: labor
and resource-intensive, low-skill and technology-intensive,
medium-skill and technology-intensive, and high-skill and
technology-intensive.

In this article we will
explore the dynamic exporting sectors of the Eurozone
countries by identifying the competitive advantages. The
statistical data used are provided by the Hellenic Statistical
Authority (ELSTAT) and the Comtrade UN (United
Nations) database; the time horizon is 2000-2014. In our
analysis, eleven Eurozone countries (EU11) were taken
under consideration: Greece, Austria, Belgium, Finland,
France, Germany, Ireland, Italy, the Netherlands, Portugal
and Spain. The comparative advantages were
calculated on a 2-digit classification base, according to
the Standard International Trade Classification (SITC rev.
3). We identified the strong comparative advantages of
each country in regard to the remaining 10 Eurozone
countries.

Increased competition and uncertainty characterise the new economy, introducing significant pressures to supply chain participants, calling for capital investments only in value adding/revenue-generating assets. The tendency of companies to expand their control through the entire supply chain seems to attract significant managerial attention. On the other hand, large manufacturer and distributor firms have developed specific competences that do not expand to all the levels of the supply chain. In order to confront the lack of knowledge and expertise companies can either outsource the specific operation or acquire a company that is specialized in the specific field. In this paper we focus on warehousing decisions and investigate three different warehousing policies and ownership structures of the warehousing facilities. INTRODUCTION The new economy is characterised by increased uncertainty and intense competition. The continuously changing market needs and the increased competition in the global markets introduce significant pressures to supply chain participants. The tendency of companies to expand their control through the entire supply chain seems to attract significant managerial attention. On the other hand flexibility associated to the ability to respond to the challenges of the changing and dynamic economic environment is highlighted as the key feature in coping successfully with the uncertainty of the new economy. In this paper, under the above mentioned perspective, we focus on inventory and warehousing decisions and operations and investigate alternative warehousing policies accompanied with different ownership structures of the warehousing facilities. Since the seminal papers of Arrow et al. (1951) and Dvoretzky et al. (1952) inventory theory has been an active area of research attracting the interest of both academics and professionals. Significant research effort has been conducted to determine the optimal inventory policies. For example, Toktay and Wein (2001) focused on the base-stock policy incorporating forecast information to determine the base-stock level that minimizes the expected steady-state inventory holding and backorders costs, assuming stationary demand. Graves (1999) and Graves and Willems (2000) developed a framework for modeling strategic safety stock incorporating non-stationary demand. Meca et al. (2004) analysed situations where a collective of firms minimizes its joint inventory by means of information sharing and cooperation. Inventory theory has also been of great importance in supply chain management. Giannoccaro et al. (2003) defined a supply chain inventory management policy utilising fuzzy set theory to model uncertainty of demand and costs. Belvaux and Wolsey (2001) used mixed-integer programming in order to handle safety stocks in multilevel supply chains. Furthermore, in the context of supply chain, procedures that combine