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The growth of logistics departments in colleges and universities has been unprecedented in the past ten years. In response to this demand, schools expanded their programs to accommodate more students at both the graduate and undergraduate levels. While schools have typically structured their logistics departments differently, they, for the most part, failed to develop their programs to more accurately reflect the multi‐disciplinary nature of supply‐chain management. The article examines the structures of logistics departments against the backdrop of teaching supply‐chain management. Strengths and weaknesses of the structures are identified with a series of recommendations set forth to help schools cope with the increased enrollments and the dynamics of the logistics field.

As in line with eco benchmarking, the purpose of this paper is to solve a location selection problem in an emerging country by applying sustainability benchmarking principles.

A hybrid multi-criteria decision-making method, fuzzy AHP and Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), is used as methodology to make sustainability benchmarking for logistics center location selection.

It is revealed that according to AHP and PROMETHEE calculations, Kemalpasa is determined as the most appropriate location from the sustainable perspectives. Torbali is specified as the worst location to construct a logistics center in terms of benchmarking criteria based on sustainability concerns. Based on these numerical results, managerial implications are presented with a sustainability benchmarking view.

The main originality of this study is integrating one of the relatively new topics, sustainability benchmarking, with a popular area, logistics center location selection.

Materials supply is one of the important elements in construction operation and a major factor affecting the quality of construction projects. Many industries look to manage materials effectively by attempting to integrate logistics processes into logistics chains of suppliers and customers. Logistics processes, being crucial for successful completion of construction projects, but in fact, auxiliary, are often entrusted to external professionals specialised in logistic services, such as logistics centres. However, this tendency is yet to be developed in construction. The purpose of this paper is to develop a simulation framework for the examination of potential improvements of logistics performance using logistics centres.

A case study approach was adopted with computer simulation using Flexsim. Data of vehicle movements were collected during construction on-site from the start of construction to “hand-over” to the building owner.

The ideal location of a logistics centre is identified using vehicle movements data collected on the site. The potential improvements of the planned centre are then evaluated by simulating various scenarios of vehicle movements. The enclosed results from the simulations indicate that using a logistics centre will reduce waste for the construction project considered.

The paper emphasises that creating a logistics centre for a project can improve construction logistics performance, by consolidating and optimizing both off-site and on-site logistics, especially when the site condition is prohibitive (small footprint with limited loading bay area). Establishing logistics centres may help find ways of making the overall construction project more effective by improving the management of materials.

Although the supply chain (SC) competition concept has emerged during the past decade as the way firms will compete in future, there is scant academic research on actual mechanisms through which such competition can occur. The purpose of this paper is to proposes interaction as the means by which competition between supply chains may be undertaken.

The paper investigates a Swedish logistics center via case study methodology to develop the idea of interaction for SC vs SC competition.

Results suggest that interaction points along organizations ' supply chains may present enough breadth to assume a role in determining how SC vs SC competition may be played out in reality.

Interaction, as proposed here, implies an emphasis on all points at which supply chains meet to request goods and services, including various points where such supply chains converge, e.g. service providers, original equipment manufacturers, etc.

Most studies dealing with competition between supply chains fall short of exploring the link between theory and corresponding practice of this evolving competition mode. Such a link is provided with the use of logistics centers.

This article reports on the current state of Common Logistics Center (CLC) adoption in Korea’s industrial complex, identifies the benefits of and barriers of adopting Common Logistics Centers, and provides recommendations for the adoption/expansion of Common Logistics Centers. The author surveyed a cross-sectional of 175 firms in the industry, followed by interviews in an industrial complex in Incheon, Korea. The author founded the benefits and barriers of Common Logistics Centers and the major factors that encourage companies’ participation.

A number of literature contributions have underlined the importance of developing value-added logistics activities or VALS in order to help improve customers’ satisfaction. However, there is usually very little attention given regarding where to perform these VALS. This study aims to: (1) identify a comprehensive set of factors which may influence the location of VALS, (2) to analyze to what extent those factors influence location decisions, and (3) to distinguish the determinants behind the location choices for distribution centers and for the kind of VALS that will be developed in these distribution centers.

In this paper, we will present a conceptual framework on the locations of VALS in view of the identifying determinants for assigning VALS to logistical centers. We argue that the optimal location of VALS is determined by complex interactions between the determinants at the level of the choice of a distribution system, distribution center location factors, and different logistical characteristics regarding products.

In the German automotive industry the supplier park concept is one of the new concepts in procurement logistics, evolved in the last years. To understand the spreading of supplier parks, it is necessary to look at actual requirements in procurement logistics in the German automotive industry and find out how supplier parks can be an answer to those requirements. For this purpose it is necessary to identify indicators describing this logistics platform. The objective of this paper is the demarcation of the supplier park concept against the concept of a freight traffic center and the concept of a distribution center. Thus, suggestions for improvements of supplier parks and first impacts for new concepts in procurement logistics can be dedicated.

The approach of this paper is to develop a descriptive model of supplier parks. The description of concepts with specific indicators has to be always the first step in dealing scientifically with new concepts emerging in practice. The paper outlines the supplier park concept in the German automotive industry with these indicators. First recommendations for the practical application of this concept are made by designing the indicators. The findings of this paper are based on an empirical investigation of the years 2000‐2002.

The findings are indicators which are useful for a description and demarcation of the supplier park concept. With these indicators the supplier park concept can be characterized and demarcated against the concept of a freight traffic center and distribution center. The description model of a supplier park delivers the theoretical framework for the development of explanation and decision models.

The indicators “objectives, participant, location, formation and operation” allow one to describe the features of supplier parks. Thus, the decision field for introducing and improving the supplier park concept is found.

In the development processes of a product’s market life cycle, there are three phases of an enterprise’s innovation: new product development, production processes, and product management. In this article, the analyses of benefit and costs, value, and profit to companies are discussed in different stages. New logistics features that appear in an enterprise’s supply chain based on innovative modeling are discussed. Then a logistics model and its technical system based on the classified logistics center are established, which are appropriate for innovative modeling within an agile supply chain. Using the basic theory and techniques of ‘extenics’, the formal conception of innovative modeling-based manufacture in logistics is presented, and the matter-element models are established. Finally, a case study demonstrates the results.

The purpose of this paper is to empirically assess the impacts of logistics learning capability on logistics service capability and organizational performance in the context of international distribution center operators (IDCOs) in Taiwan.

Data for this study were collected by questionnaire survey. A two-steps structural equation modeling (SEM) approach was performed in this study to test the research hypotheses. The first step is performing confirmatory factor analysis (CFA) to assess the validity of the measurement model. The second step proceeds to estimate the structural model between latent variables.

A five-dimension scale including open-mindedness (O), commitment to learning (C), system perspective (E), partner learning (A), and shared vision (N) was proposed in this study and was supported by CFA analysis to measure IDCOs’ logistics learning capability in this study. Results of SEM indicated that logistics learning capability is positively related to logistics service capability, whereas logistics service capability is also positively related to organizational performance. Although logistics learning capability has no direct relationship to organizational performance, we found it indirectly affects organizational performance via logistics service capability.

This study primarily focusses on the effect of logistics learning on organizational performance. Future research could incorporate environmental uncertainty as a moderator to assess its impact on the relationship between logistics learning capability and organizational performance.

IDCOs can enhance customer service and financial performance by developing logistics learning capability and specifically focussing efforts on supply chain partner learning.

This study presents the first to examine the effects of logistics learning capability on logistics service capability and organizational performance in the context of IDCOs. Particularly, this study proposes a five-dimension logistics learning capability scale from a supply chain perspective.

The purpose of this paper is to propose a disaster logistics center location selection decision support system, based on analytic hierarchy/fuzzy analytic hierarchy process methods, which will serve to fulfill the needs of disaster victims and rescue teams after a possible earthquake, and to implement the proposed systems for Istanbul.

Determining the appropriate location from among the possibilities by taking many sophisticated and inter‐related processes and parameters into consideration under stringent constraints is one of the keystones of logistics. Disaster logistics center location selections are extremely complex and vital. In this paper, analytic hierarchy/fuzzy analytic hierarchy process methods are used to compose a decision support system for determining the location of disaster logistics centers. The criteria and the weighting for the criteria that are used are determined via a questionnaire technique applied to specialists working in the Istanbul Center of Disaster Coordination.

Results gathered from the implementation of the proposed models to the chosen case illustrate that systems successfully determine the location, and both models point out the same result with different weights.

The paper introduces two disaster logistics center location selection decision support systems (fuzzy and crisp) and presents an empirical case study of the proposed models for Istanbul. The proposed model and outcomes from the application may shed light on future work, especially in the field of disaster logistics management.